Dataset: Machine Learning–Accelerated Prediction of Amorphization Enthalpy in Ionic Compounds

Description This dataset contains amorphization enthalpy data for a variety of ionic compounds, evaluated using both Density Functional Theory (DFT) and a Graph Neural Network (GNN) model. The data is presented in two CSV files, each with key information about the chemical formulas, material IDs, and corresponding amorphization enthalpies. Files 1. dft_enthalpy_data.csv This file contains the following columns: Formula: The chemical formula of the compound. material_id: The unique ID of the material in the Materials Project database. Amorphization Enthalpy (eV): The amorphization enthalpy of the compound, evaluated using Density Functional Theory (DFT). 2. GNN_enthalpy_data.csv This file contains the following columns: Formula: The chemical formula of the compound. material_id: The unique ID of the material in the Materials Project database. Amorphization Enthalpy (eV): The amorphization enthalpy of the compound, evaluated using a Graph Neural Network (GNN) model.